Yanghui Kang

1.6k total citations · 2 hit papers
14 papers, 810 citations indexed

About

Yanghui Kang is a scholar working on Ecology, Global and Planetary Change and Plant Science. According to data from OpenAlex, Yanghui Kang has authored 14 papers receiving a total of 810 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Ecology, 10 papers in Global and Planetary Change and 7 papers in Plant Science. Recurrent topics in Yanghui Kang's work include Remote Sensing in Agriculture (12 papers), Plant Water Relations and Carbon Dynamics (6 papers) and Land Use and Ecosystem Services (4 papers). Yanghui Kang is often cited by papers focused on Remote Sensing in Agriculture (12 papers), Plant Water Relations and Carbon Dynamics (6 papers) and Land Use and Ecosystem Services (4 papers). Yanghui Kang collaborates with scholars based in United States, Spain and Italy. Yanghui Kang's co-authors include Mutlu Özdoğan, Zhou Zhang, Yuchi Ma, Martha C. Anderson, Zhiwei Ye, Christopher Hain, Xiaojin Zhu, Michael Marshall, Vincenzo Magliulo and Yun Yang and has published in prestigious journals such as Remote Sensing of Environment, Remote Sensing and Environmental Research Letters.

In The Last Decade

Yanghui Kang

13 papers receiving 782 citations

Hit Papers

Corn yield prediction and uncertainty analysis based on r... 2020 2026 2022 2024 2021 2020 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Corn yield prediction and uncertainty analysis based on remotely sensed variables using a Bayesian neural network approach
    2021 181 citations Yuchi Ma, Zhou Zhang et al. Remote Sensing of Environment profile →
  2. Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest
    2020 166 citations Yanghui Kang, Mutlu Özdoğan et al. Environmental Research Letters profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yanghui Kang United States 12 519 395 281 200 126 14 810
Wen Zhuo China 16 425 0.8× 298 0.8× 287 1.0× 170 0.8× 131 1.0× 31 834
Jialu Xu China 12 387 0.7× 344 0.9× 161 0.6× 138 0.7× 150 1.2× 40 872
Jichong Han China 13 617 1.2× 507 1.3× 259 0.9× 171 0.9× 190 1.5× 29 990
Jie Dong China 15 479 0.9× 234 0.6× 271 1.0× 138 0.7× 76 0.6× 33 780
Jihua Meng China 18 736 1.4× 324 0.8× 463 1.6× 329 1.6× 118 0.9× 47 1.1k
K. R. Manjunath India 19 560 1.1× 250 0.6× 267 1.0× 222 1.1× 85 0.7× 46 966
Claire Marais Sicre France 7 445 0.9× 201 0.5× 209 0.7× 183 0.9× 57 0.5× 8 618
Masayasu Maki Japan 14 429 0.8× 250 0.6× 268 1.0× 217 1.1× 51 0.4× 42 638
Francesco Nutini Italy 15 622 1.2× 262 0.7× 389 1.4× 320 1.6× 42 0.3× 31 908
Jingfeng Huang China 9 470 0.9× 291 0.7× 186 0.7× 210 1.1× 55 0.4× 18 833

Countries citing papers authored by Yanghui Kang

Since Specialization
Citations

This map shows the geographic impact of Yanghui Kang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yanghui Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanghui Kang more than expected).

Fields of papers citing papers by Yanghui Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yanghui Kang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yanghui Kang. The network helps show where Yanghui Kang may publish in the future.

Co-authorship network of co-authors of Yanghui Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Yanghui Kang. A scholar is included among the top collaborators of Yanghui Kang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yanghui Kang. Yanghui Kang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Kang, Yanghui, et al.. (2025). CEDAR-GPP: spatiotemporally upscaled estimates of gross primary productivity incorporating CO 2 fertilization. Earth system science data. 17(6). 3009–3046.
2.
Kang, Yanghui, et al.. (2024). Using automated machine learning for the upscaling of gross primary productivity. Biogeosciences. 21(10). 2447–2472. 8 indexed citations
3.
Wan, Liang, Youngryel Ryu, Benjamin Dechant, et al.. (2024). Correcting confounding canopy structure, biochemistry and soil background effects improves leaf area index estimates across diverse ecosystems from Sentinel-2 imagery. Remote Sensing of Environment. 309. 114224–114224. 14 indexed citations
4.
Verfaillie, Joseph, Ariane Arias‐Ortiz, Daphne Szutu, et al.. (2024). Net fluxes of broadband shortwave and photosynthetically active radiation complement NDVI and near infrared reflectance of vegetation to explain gross photosynthesis variability across ecosystems and climate. Remote Sensing of Environment. 307. 114123–114123. 21 indexed citations
5.
Zhou, Junxiong, Qi Yang, Licheng Liu, et al.. (2023). A deep transfer learning framework for mapping high spatiotemporal resolution LAI. ISPRS Journal of Photogrammetry and Remote Sensing. 206. 30–48. 17 indexed citations
6.
Kang, Yanghui, Feng Gao, Martha C. Anderson, et al.. (2022). Evaluation of satellite Leaf Area Index in California vineyards for improving water use estimation. Irrigation Science. 40(4-5). 531–551. 25 indexed citations
7.
Kang, Yanghui, Mutlu Özdoğan, Feng Gao, et al.. (2021). A data-driven approach to estimate leaf area index for Landsat images over the contiguous US. Remote Sensing of Environment. 258. 112383–112383. 57 indexed citations
8.
Ma, Yuchi, Zhou Zhang, Yanghui Kang, & Mutlu Özdoğan. (2021). Corn yield prediction and uncertainty analysis based on remotely sensed variables using a Bayesian neural network approach. Remote Sensing of Environment. 259. 112408–112408. 181 indexed citations breakdown →
9.
Liu, Zhe, Diyou Liu, Yanghui Kang, et al.. (2020). Early Identification of Seed Maize and Common Maize Production Fields Using Sentinel-2 Images. Remote Sensing. 12(13). 2140–2140. 35 indexed citations
10.
Kang, Yanghui, Mutlu Özdoğan, Xiaojin Zhu, et al.. (2020). Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest. Environmental Research Letters. 15(6). 64005–64005. 166 indexed citations breakdown →
11.
Kang, Yanghui & Mutlu Özdoğan. (2019). Field-level crop yield mapping with Landsat using a hierarchical data assimilation approach. Remote Sensing of Environment. 228. 144–163. 131 indexed citations
12.
13.
Marshall, Michael, et al.. (2016). Global assessment of Vegetation Index and Phenology Lab (VIP) and Global Inventory Modeling and Mapping Studies (GIMMS) version 3 products. Biogeosciences. 13(3). 625–639. 34 indexed citations
14.
Kang, Yanghui, Mutlu Özdoğan, Samuel C. Zipper, et al.. (2016). How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment. Remote Sensing. 8(7). 597–597. 110 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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